Charging Management System

Abstract

To enable charging to be made based on an intention of a driver.SOLUTION: A processor of a charging management system executes processes to: acquire meteorological prediction information indicating meteorological prediction; estimate a reduction amount of SOC of an on-vehicle battery in the future in an arbitrary vehicle; acquire user intention information indicating user intension with respect to whether a user thinks much of charging a vehicle at a charging station of electricity generated from renewable energy; and derives a charging plan indicating a combination of charging timing and a charging station in the future which offers a relatively inexpensive unit charging rate taking into consideration the intention of the user on the basis of correlated information stored in a storage device, the acquired meteorological prediction information, the estimated reduction amount of SOC and the acquired user intention information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a charge management system that manages charging of an in-vehicle battery. [Background technology]

[0002] For example, Patent Document 1 discloses an information processing device for a vehicle that provides information about charging facilities. The information processing device accumulates a driving behavior history of the vehicle and generates driving characteristic information based on the accumulated driving behavior history. The information processing device then provides the driver with information about a charging facility selected from a group of charging facilities based on the driving characteristic information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-234924 Summary of the Invention [Problem to be solved by the invention]

[0004] Incidentally, when charging an onboard battery at a charging station, some drivers are environmentally conscious and prefer to charge at charging stations that supply electricity generated from renewable energy sources.

[0005] Therefore, an object of the present invention is to provide a charge management system that enables charging based on the driver's preferences. [Means for solving the problem]

[0006] In order to solve the above problem, a charge management system according to one embodiment of the present invention includes: a storage device that stores in advance correlation information in which a plurality of charging stations, weather information at the locations of the charging stations at any timing, and a charging unit price at the charging stations at any timing are associated with each other for each of the plurality of charging stations and the plurality of weather information; a control device; Equipped with The control device one or more processors; one or more memories coupled to said processor; and In the correlation information, whether the source of power generation at the charging station is renewable energy or not is associated with each charging station, The processor: obtaining weather forecast information indicative of a weather forecast; Estimating a future decrease in SOC of an on-board battery in a given vehicle; Acquiring user preference information indicating whether a user values ​​charging at a charging station where the source of power generation is renewable energy; deriving a charging plan that indicates a combination of future charging timings and charging locations that will result in a relatively low charging unit price while reflecting the user's preference, based on the correlation information stored in the storage device, the acquired weather forecast information, the estimated SOC decrease amount, and the acquired user preference information; Execute the process including. [Effects of the Invention]

[0007] According to the present invention, charging can be performed in accordance with the driver's preferences. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a schematic diagram showing the configuration of a charge management system according to this embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of correlation information. [Figure 3]FIG. 3 is a diagram illustrating an example of a user orientation coefficient table. [Figure 4] FIG. 4 is a diagram illustrating an example of a charging unit price coefficient table. [Figure 5] FIG. 5 is a diagram illustrating an example of a natural disaster coefficient table. [Figure 6] FIG. 6 is a diagram showing an example of weather forecast information acquired by the weather forecast information acquisition unit. [Figure 7] FIG. 7 is a diagram showing an example of the SOC decrease amount derived by the SOC decrease amount estimating unit. [Figure 8] FIG. 8 is a diagram illustrating an example of derivation of the index. [Figure 9] FIG. 9 is a diagram illustrating an example of derivation of a charging plan. [Figure 10] FIG. 10 is a diagram illustrating an example of derivation of a charging plan. [Figure 11] FIG. 11 is a diagram illustrating an example of derivation of a charging plan. [Figure 12] FIG. 12 is a diagram showing an example of derivation of another charging plan. [Figure 13] FIG. 13 is a diagram showing an example of derivation of another charging plan. [Figure 14] FIG. 14 is a flowchart illustrating the operation of the control device in relation to deriving a charging plan. [Figure 15] FIG. 15 is a flowchart illustrating the flow of the index derivation process. [Figure 16] FIG. 16 is a flowchart illustrating the flow of the charging plan derivation process. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. Specific dimensions, materials, numerical values, etc. shown in the embodiments are merely examples for facilitating understanding of the invention and do not limit the present invention unless otherwise specified. In this specification and drawings, elements having substantially the same functions and configurations are designated by the same reference numerals to avoid redundant explanation, and elements not directly related to the present invention are not shown.

[0010] 1 is a schematic diagram showing the configuration of a charging management system 1 according to this embodiment. The charging management system 1 includes a vehicle 10 and a plurality of charging stations 12.

[0011] Vehicle 10 is, for example, an electric vehicle or a hybrid electric vehicle, and includes a motor as a drive source for traveling. Vehicle 10 is equipped with an on-board battery 20. On-board battery 20 is, for example, a lithium-ion battery, which is a secondary battery that can be charged and discharged. On-board battery 20 supplies power to the motor that is the drive source.

[0012] The charging stand 12 is an example of a power source external to the vehicle 10. The charging stand 12 is installed in various locations. The charging stand 12 is configured to supply power to the vehicle 10, for example, by connecting a charging connector (not shown) to the vehicle 10. The vehicle 10 is configured to receive power from an external power source, for example, by connecting the charging connector to a charging port (not shown). When power is supplied to the vehicle 10 from outside the vehicle 10, the on-board battery 20 is charged.

[0013] Charging stations 12 are divided into, for example, renewable energy charging stations and non-renewable energy charging stations. A renewable energy charging station is a charging station 12 that supplies electric power generated using renewable energy to the vehicle 10. In other words, a renewable energy charging station is a charging station 12 that generates electric power from renewable energy.

[0014] Renewable energy is energy that can be expected to be constantly replenished even if consumed. Examples of renewable energy include natural energy such as solar, wind, hydroelectric, geothermal, and tidal. Note that renewable energy is not limited to natural energy, and may include any energy that is not a natural phenomenon but can be expected to be constantly replenished even if consumed, such as biomass.

[0015] Renewable energy charging stations generate electricity using renewable energy in the area where they are installed. For example, solar charging stations 12 are installed in areas with relatively high annual average solar radiation and generate electricity using sunlight shining on the area where they are installed. Wind power charging stations 12 are installed in areas with relatively high annual average wind speeds and generate electricity using wind power in the area where they are installed. Hydropower charging stations 12 are installed in areas with abundant water resources and generate electricity using the potential energy of water in the area where they are installed.

[0016] Note that the amount of power generated at a renewable energy charging station may not be stable due to, for example, variations in the amount of solar radiation over time, variations in wind speed over time, variations in the amount of water over time, etc. The renewable energy charging station may be provided with a battery that stores the generated power, thereby stabilizing the power that can be supplied to vehicle 10.

[0017] Furthermore, a renewable energy charging station is not limited to a charging station in which all of the power supplied to the vehicle 10 is derived from renewable energy. For example, consider a charging station that supplies to the vehicle 10 a mixture of power from distributed power sources such as solar power generation and power from a power grid. The power from the power grid contains a large amount of power derived from non-renewable energy sources, as described below. Even if the power supplied to the vehicle 10 contains power derived from non-renewable energy sources, the charging station may be considered a renewable energy charging station if a predetermined percentage or more, for example, 50% or more, of the power supplied to the vehicle 10 is derived from renewable energy. For example, the charging station may be considered a renewable energy charging station if the ratio of the amount of power supplied to the vehicle 10 from distributed power sources such as solar power generation at the charging station to the total amount of power supplied to the vehicle 10 from the charging station is a predetermined percentage or more.

[0018] A non-renewable energy charging station is a charging station 12 that supplies electric power obtained from energy other than renewable energy to a vehicle 10. In other words, a non-renewable energy charging station is a charging station 12 that does not generate electricity from renewable energy.

[0019] Non-renewable energy is, for example, energy obtained by burning fossil resources such as coal, oil or gasoline.

[0020] A non-renewable energy charging station supplies, for example, electric power generated in-house by consuming fossil fuels to the vehicle 10. A charging station 12 that supplies electric power from a power grid that includes a large amount of electric power derived from non-renewable energy to the vehicle 10 may be classified as a non-renewable energy charging station.

[0021] If the proportion of renewable energy in the power supplied to the vehicle 10 is less than a predetermined proportion, for example, less than 50%, the charging station may be considered to be a non-renewable energy charging station.

[0022] The charging station 12 includes a station communication unit 30, a station storage device 32, and a station control device 34. The station communication unit 30 can communicate with the vehicle 10 via a communication network 40 such as the Internet.

[0023] The stand storage device 32 is composed of a nonvolatile storage element. The nonvolatile storage element may include an electrically readable and writable nonvolatile storage element such as a flash memory. The stand storage device 32 stores, for example, information that distinguishes whether the charging stand 12 having the stand storage device 32 is a renewable energy charging stand or a non-renewable energy charging stand. Furthermore, if the charging stand 12 is a renewable energy charging stand, the stand storage device 32 stores information that distinguishes the type of renewable energy used at the charging stand 12.

[0024] In addition, in a renewable energy charging station that uses multiple types of renewable energy as its source of electricity, the renewable energy source with the highest proportion of renewable energy may be determined as the type of renewable energy at the renewable energy charging station.

[0025] The station control device 34 has a processor and memory (not shown) and controls each part of the charging station 12. The station control device 34 can also transmit information stored in the station storage device 32, such as information identifying whether the station is a renewable energy charging station, to the vehicle 10 via the station communication unit 30.

[0026] The driver of the vehicle 10 can charge the on-board battery 20 at any one of the charging stations 12 located in each area.

[0027] Here, some drivers prefer charging at renewable energy charging stations over non-renewable energy charging stations, while other drivers do not care about charging at renewable energy charging stations. In this way, drivers have different preferences regarding charging.

[0028] Hereinafter, passengers such as a driver of the vehicle 10 are referred to as users of the charging management system 1 of this embodiment. In addition, whether or not a user places importance on charging at charging stations where power generation originates from renewable energy, in other words, renewable energy charging stations, is referred to as user orientation.

[0029] The charging management system 1 of this embodiment derives a future charging plan that reflects the user's preferences and results in a relatively low charging cost. The charging plan indicates a combination of future charging timing and charging location. For example, the charging management system 1 derives a charging plan that indicates which charging station 12 is best to use and on which day within a period of one week from now. The derived charging plan is presented to the user, allowing the user to charge at an appropriate charging station 12 at an efficient timing that suits the user's preferences. A vehicle 10 that realizes the charging management system 1 will be described in detail below.

[0030] In addition to the on-board battery 20, the vehicle 10 is equipped with a vehicle communication unit 50, a user interface 52, a storage device 54, and a control device 56. The vehicle communication unit 50 can communicate with each charging station 12 via the communication network 40. The vehicle communication unit 50 can also communicate with a weather server 60 via the communication network 40.

[0031] The weather server 60 manages weather information for various locations. For example, the weather server 60 collects and stores current weather information for various locations. The weather server 60 also analyzes the stored past weather information to forecast future weather and generate weather forecast information indicating the forecast. The weather server 60 can provide the vehicle 10 with current weather information and weather forecast information for various locations via the communication network 40.

[0032] The weather information and weather forecast information may include, for example, information on the weather, solar radiation, wind speed, and rainfall in each location. The solar radiation, wind speed, and rainfall may be accumulated at predetermined intervals, such as every hour.

[0033] The user interface 52 of the vehicle 10 includes a display device 70 such as a liquid crystal display or an organic EL display. The display device 70 displays various images or various information. In addition to the display device 70, the user interface 52 may also include an output device, such as a speaker, that presents various information to the user. The user interface 52 may also include an input device, such as a touch panel, that accepts user operations.

[0034] The storage device 54 is configured with a nonvolatile storage element. The nonvolatile storage element may include an electrically readable and writable nonvolatile storage element such as a flash memory. The storage device 54 stores user preference information 80, correlation information 82, a user preference coefficient table 84, a charging unit price coefficient table 86, and a natural disaster coefficient table 88.

[0035] User preference information 80 is information indicating a user preference as to whether or not charging at a renewable energy charging station is important. Hereinafter, prioritizing charging at a renewable energy charging station may be referred to as "environmental priority." On the other hand, not being particular about the type of charging station 12 may be referred to as "no environmental priority." The user inputs information indicating "environmental priority" or "no environmental priority" in advance via input device 72. As a result, the input result of "environmental priority" or "no environmental priority" is stored in advance in storage device 54 as user preference information 80.

[0036] The user preference information 80 is not limited to being stored based on user input. For example, each time charging is performed at a charging station 12, the type of charging station 12 may be stored in the storage device 54, and the control device 56 may generate the user preference information 80 based on the proportion of types of charging stations 12 used in the past.

[0037] The correlation information 82 is information in which the charging stand 12, weather information at any timing at the location of the charging stand 12, and the charging cost at any timing at the charging stand 12 are associated with each of the multiple charging stands 12 and multiple pieces of weather information. In the correlation information 82, the charging cost is associated with each combination of an individual charging stand 12 and a value of one piece of weather information from the multiple pieces of weather information.

[0038] Fig. 2 is a diagram showing an example of the correlation information 82. In Fig. 2, renewable energy charging stations are abbreviated as "renewable energy," and non-renewable energy charging stations are abbreviated as "non-renewable energy." The items and numerical values ​​shown in Fig. 2 are merely examples and are not limited to these examples.

[0039] The charging stand identifier is information that identifies the charging stand 12. The power generation type indicates the original energy used to generate the power supplied by the charging stand 12. In the correlation information, for example, solar radiation, wind speed, and rainfall are set as weather information. Solar radiation is the amount of radiant energy that a unit area receives from the sun per unit time. Wind speed is the speed at which air moves as wind. Rainfall indicates the amount of rain that falls per unit time. The charging cost indicates the price per unit amount of power supplied by the charging stand 12.

[0040] In the example of Figure 2, charging station "A" is a solar renewable energy charging station. At charging station "A," the charging price is set in correspondence with the amount of solar radiation, and the charging price is determined for each value of the amount of solar radiation.

[0041] Charging station "B" is a renewable energy charging station for wind power. At charging station "B," the charging cost is set according to the wind speed, and the charging cost is determined for each wind speed.

[0042] Charging station "C" is a hydroelectric renewable energy charging station. At charging station "C," the charging cost is set according to the amount of rainfall, and the charging cost is determined for each rainfall value.

[0043] Charging station "D" is a non-renewable thermal energy charging station. Charging station "D" has a fixed charging price regardless of the amount of solar radiation, wind speed, or rainfall.

[0044] Here, the charge management system 1 uses the following "indexes" to derive a charging plan. As will be described in detail later, the control device 56 derives the "indexes" for each charging station 12 and for each day in a predetermined future period. The control device 56 derives a charging plan that increases the derived "indexes."

[0045] The "index" includes and is the multiplication of the "user preference coefficient," the "charging unit price coefficient," and the "natural disaster coefficient," as shown in the following formula (1). "Indicator" = "User preference coefficient" × "Charging unit price coefficient" × "Natural disaster coefficient" (1)

[0046] The "index" may include at least the user preference coefficient and the charging unit price coefficient, and the natural disaster coefficient may be omitted.

[0047] The user preference coefficient indicates a weighting of the user preference, and is derived based on the user preference information 80 and the user preference coefficient table 84 stored in the storage device 54.

[0048] Fig. 3 is a diagram showing an example of the user orientation coefficient table 84. In Fig. 3, renewable energy charging stations are abbreviated as "renewable energy," and non-renewable energy charging stations are abbreviated as "non-renewable energy." Note that the numerical values ​​shown in Fig. 3 are merely examples and are not limited to these examples.

[0049] In the user inclination coefficient table 84, a user inclination coefficient is set for each combination of the type of charging station 12 and the user inclination.

[0050] In the example of Fig. 3, in the case of a user orientation of "environmental priority," a user orientation coefficient of "2" is set for the "renewable energy" charging station 12, and a user orientation coefficient of "1" is set for the "non-renewable energy" charging station 12. On the other hand, in the case of a user orientation of "no environmental priority," a user orientation coefficient of "1" is set for the "renewable energy" charging station 12, and a user orientation coefficient of "2" is set for the "non-renewable energy" charging station. In this way, the user orientation coefficient table 84 is set so that a charging station 12 that is in line with the user orientation has a larger user orientation coefficient than other charging stations 12.

[0051] The control device 56 acquires the user orientation information 80 from the storage device 54, and derives a user orientation coefficient from the user orientation information 80 by referring to the user orientation coefficient table 84. For example, if the user orientation information 80 indicates "environmental priority given" and the charging station 12 from which the "index" is derived is a "renewable energy" charging station 12, the user orientation coefficient table 84 is referred to, and a user orientation coefficient of "2" is derived.

[0052] In the example of Fig. 3, when "environmental priority is given," the user inclination coefficient is set so that the ratio of "renewable energy" to "non-renewable energy" is 2:1. However, the user inclination coefficient is not limited to this example, and may be set so that the ratio of "renewable energy" to "non-renewable energy" is any ratio, such as a 1:0 ratio or a 7:3 ratio.

[0053] The charging unit price coefficient indicates a weighting of the charging unit price at the charging station 12. As will be described later, the control device 56 acquires weather forecast information from the weather server 60 and estimates the charging unit price at the charging station 12 based on the weather forecast information and correlation information 82. The charging unit price coefficient is derived based on the estimated charging unit price and a charging unit price coefficient table 86.

[0054] Fig. 4 is a diagram showing an example of the charging unit price coefficient table 86. Note that the numerical values ​​shown in Fig. 4 are merely examples, and the present invention is not limited to these examples.

[0055] In the charging unit price coefficient table 86, the charging unit price of the charging station 12 and the charging unit price coefficient are set in association with each other.

[0056] In the example of FIG. 4, when the charging unit price is less than 10, the charging unit price coefficient is set to "2." When the charging unit price is 10 or more and less than 15, the charging unit price coefficient is set to "1.6." When the charging unit price is 15 or more and less than 20, the charging unit price coefficient is set to "1.2." When the charging unit price is 20 or more, the charging unit price coefficient is set to "0.8." In this way, in the charging unit price coefficient table 86, the lower the charging unit price, the larger the charging unit price coefficient is set.

[0057] The control device 56 derives a charging unit price coefficient from the estimated charging unit price by referring to the charging unit price coefficient table 86. For example, if the estimated charging unit price is "10", a charging unit price coefficient of "1.6" is derived.

[0058] The natural disaster coefficient indicates a weighting of the degree of risk of a natural disaster at the location of the charging station 12. An example of a natural disaster is, for example, a typhoon, but is not limited to this example. The control device 56 acquires weather forecast information for the charging station 12 from the weather server 60. The control device 56 derives the natural disaster coefficient based on the weather forecast information and the natural disaster coefficient table 88.

[0059] Fig. 5 is a diagram showing an example of the natural disaster coefficient table 88. Note that the numerical values ​​shown in Fig. 5 are merely examples, and the present invention is not limited to these examples.

[0060] Weather information and natural disaster coefficients are associated and set in the natural disaster coefficient table 88. For example, in the natural disaster coefficient table 88, wind speed and natural disaster coefficients are associated with each other among the weather information, and rainfall and natural disaster coefficients are associated with each other among the weather information.

[0061] In the example of Figure 5, if the wind speed is less than 10, the natural disaster coefficient is set to "3." If the wind speed is between 10 and 25, the natural disaster coefficient is set to "2." If the wind speed is 25 or more, the natural disaster coefficient is set to "1."

[0062] Additionally, if the rainfall is less than 10, the natural disaster coefficient is set to "3." If the rainfall is between 10 and 20, the natural disaster coefficient is set to "2." If the rainfall is 20 or more, the natural disaster coefficient is set to "1."

[0063] In this way, the natural disaster coefficient table 88 is set so that the lower the risk of natural disasters, the larger the natural disaster coefficient.

[0064] The control device 56 refers to the natural disaster coefficient table 88 and derives a natural disaster coefficient using the acquired weather forecast information as weather information in the natural disaster coefficient table 88. For example, if the wind speed is less than 10 and the rainfall is less than 10, a natural disaster coefficient of "3" is derived.

[0065] For example, if wind speed is less than 10 and rainfall is between 10 and 20, a natural disaster coefficient of "2" is derived. In this case, if wind speed and rainfall result in different natural disaster coefficients, the natural disaster coefficient with the smaller natural disaster coefficient is derived. However, if priorities are set for wind speed and rainfall, and the natural disaster coefficient based on wind speed differs from the natural disaster coefficient based on rainfall, the natural disaster coefficient with the higher priority may be derived. Furthermore, the natural disaster coefficient may be associated with only one of wind speed and rainfall.

[0066] The control device 56 multiplies the user preference coefficient, the charging unit price coefficient, and the natural disaster coefficient to derive an "index."

[0067] The "index" may be a value obtained by multiplying a user preference coefficient, a charging unit price coefficient, and a natural disaster coefficient, and then multiplying the result by a charging time coefficient. Since the charging time becomes shorter as the charging current increases, the charging time coefficient is set based on the charging current at the charging station 12. The charging time coefficient is set to a larger value as the charging time becomes shorter, in other words, as the charging current becomes larger. By including the charging time coefficient in the "index," a more effective charging plan can be derived.

[0068] 1 , the control device 56 includes one or more processors 90 and one or more memories 92 connected to the processors 90. The memories 92 include a ROM in which programs and the like are stored and a RAM as a work area. The processor 90 cooperates with the programs stored in the memory 92 to control each part of the vehicle 10.

[0069] By executing the program, the processor 90 also functions as a correlation information generation unit 100, a weather forecast information acquisition unit 102, an SOC decrease amount estimation unit 104, a user preference information acquisition unit 106, an index derivation unit 108, and a charging plan derivation unit 110. The SOC (State Of Charge) indicates the charging rate of the in-vehicle battery 20, which is the current charging capacity relative to the full charging capacity, expressed as a percentage.

[0070] The correlation information generating unit 100 generates the correlation information 82 as follows, and stores the generated correlation information 82 in the storage device 54.

[0071] The correlation information generating unit 100 acquires the route actually traveled by the vehicle 10 from a navigation device or the like. The correlation information generating unit 100 extracts charging stations 12 based on the route actually traveled.

[0072] For example, the correlation information generation unit 100 determines whether there is a passing route that has been passed through a predetermined number of times or more within a predetermined period. The predetermined period and the predetermined number of times may be set to any value. If there is a passing route that has been passed through a predetermined number of times or more within the predetermined period, the correlation information generation unit 100 extracts multiple charging stations 12 around the passing route. If there is no passing route that has been passed through a predetermined number of times or more within the predetermined period, the correlation information generation unit 100 extracts multiple charging stations 12 around the user's home.

[0073] The correlation information generation unit 100 communicates with the extracted charging station 12 via the vehicle communication unit 50 and acquires the charging price at a specific timing at the charging station 12. The specific timing can be set arbitrarily, for example, at noon on the previous day.

[0074] The correlation information generation unit 100 communicates with the weather server 60 via the vehicle communication unit 50 and acquires weather information at specific times for the location of the charging station 12. The correlation information generation unit 100 acquires charging prices and weather information at various specific times. The correlation information generation unit 100 also acquires charging prices and weather information for each of the extracted charging stations 12.

[0075] The correlation information generation unit 100 associates the extracted charging stations 12, the acquired charging unit price at the specific timing, and the acquired weather information at the specific timing to generate correlation information 82. In this manner, the correlation information 82 shown in FIG. 2 is generated. The correlation information generation unit 100 stores the generated correlation information 82 in the storage device 54.

[0076] Here, the charging stations 12 extracted by the correlation information generating unit 100 are assumed to be charging stations 12 that the user is likely to use, and therefore may be candidates for charging stations 12 to be presented in a charging plan that is derived later. Such charging stations 12 may be referred to as candidate charging stations 12.

[0077] When deriving a charging plan, the weather forecast information acquisition unit 102 communicates with the weather server 60 via the vehicle communication unit 50 to acquire weather forecast information for a predetermined period in an area that is the subject of the weather forecast and that includes the locations of the candidate charging stations 12. The predetermined period corresponds to a period for deriving a charging plan, which will be described later. Hereinafter, this predetermined period, i.e., the period for deriving a charging plan, may be referred to as a plan derivation period. This plan derivation period is, for example, a period of one week from the next day, but is not limited to this example and may be any period.

[0078] Fig. 6 is a diagram showing an example of weather forecast information acquired by the weather forecast information acquisition unit 102. In the example of Fig. 6, the next day is October 8th, and the plan derivation period is from October 8th to October 14th. Note that the dates and values ​​shown in Fig. 6 are merely examples, and are not limited to these examples.

[0079] In the example of FIG. 6 , the weather forecast information acquisition unit 102 acquires, as weather forecast information, predicted values ​​of solar radiation, predicted values ​​of wind speed, and predicted values ​​of rainfall for each day from October 8 to October 14. For example, the predicted values ​​of solar radiation are assumed to be "20," "10," "30," "5," "20," "10," and "30" in order from October 8 onwards. The predicted values ​​of wind speed are assumed to be "0," "2," "5," "2," "15," "2," and "0" in order from October 8 onwards. The predicted values ​​of rainfall are assumed to be "0," "0," "2," "8," "0," "8," and "0" in order from October 8 onwards. This weather forecast information is used to estimate the future unit price of charging at the candidate charging station 12, as will be described later.

[0080] When deriving a charging plan, the SOC decrease amount estimation unit 104 estimates the future decrease amount of the SOC of the in-vehicle battery 20. Hereinafter, the decrease amount of the SOC may be referred to as the SOC decrease amount.

[0081] For example, the SOC decline amount estimation unit 104 derives the SOC decline amount for the current day every day and stores it in the storage device 54. The SOC decline amount estimation unit 104 analyzes the daily SOC decline amount stored in this manner and estimates the future SOC decline amount. The SOC decline amount estimation unit 104 estimates the daily SOC decline amount within the plan derivation period.

[0082] Fig. 7 is a diagram showing an example of the SOC decrease amount derived by the SOC decrease amount estimation unit 104. In the example of Fig. 7, the next day is October 8th, and the plan derivation period is from October 8th to October 14th. Note that the dates and values ​​illustrated in Fig. 7 are merely examples, and are not limited to these examples.

[0083] In the example of Fig. 7, the SOC decrease amount estimation unit 104 estimates the SOC decrease amount for each day from October 8 to October 14. As a result of the estimation, the SOC decrease amounts are assumed to be "20", "20", "20", "20", "20", "10", and "30" in order from October 8 onwards. These SOC decrease amounts are used when deriving a charging plan, as will be described later.

[0084] The SOC decrease amount estimation unit 104 may also estimate the use of the vehicle 10 on each day for which the SOC decrease amount is estimated. In the example of Fig. 7, the uses of the vehicle 10 are assumed to be "commuting," "commuting," "commuting," "commuting," "commuting," "city riding," and "leisure" in that order from October 8 onwards. The SOC decrease amount differs depending on these uses.

[0085] The user-oriented information acquiring unit 106 acquires the user-oriented information 80. For example, the user-oriented information acquiring unit 106 acquires the user-oriented information 80 in advance through input by the user via the input device 72, and stores the acquired user-oriented information 80 in the storage device 54.

[0086] In addition, the user preference information acquisition unit 106 may acquire the type of charging station 12 each time charging is performed at the charging station 12, and derive the user preference information 80 based on, for example, the proportion of types of charging stations 12 that have been used in the past.

[0087] The index derivation unit 108 derives an "index" in order to derive a charging plan. Hereinafter, the derivation of the "index" will be described with reference to FIG.

[0088] Fig. 8 is a diagram illustrating an example of derivation of an index. In the example of Fig. 8, the next day is October 8th, and the plan derivation period is from October 8th to October 14th. Note that the dates and values ​​illustrated in Fig. 8 are merely examples, and are not limited to these examples.

[0089] The index derivation unit 108 derives the charging unit price based on the weather forecast information acquired by the weather forecast information acquisition unit 102 and the correlation information 82 stored in the storage device 54. The index derivation unit 108 derives the charging unit price for each date within the plan derivation period and for each candidate charging station 12.

[0090] For example, the charging cost at charging station "A" on October 8th is derived as follows. With reference to the correlation information 82 in FIG. 2, charging station "A" is a solar renewable energy charging station. Furthermore, as shown in FIG. 6, the amount of solar radiation in the weather forecast information for October 8th is "20." This amount of solar radiation "20" in the weather forecast information corresponds to the amount of solar radiation "20" in the weather information in the correlation information 82 in FIG. 2. Furthermore, as shown in FIG. 2, the charging cost corresponding to the amount of solar radiation "20" at charging station "A" is "10." Therefore, as shown in FIG. 8, a charging cost of "10" is derived for charging station "A" on October 8th.

[0091] The charging cost for other dates within the plan derivation period and for other charging stations 12 among the candidate charging stations 12 are derived in the same manner as the charging cost for charging station "A" on October 8th.

[0092] Furthermore, the index derivation unit 108 derives a charging unit price coefficient based on the charging unit price and charging unit price coefficient table 86. The index derivation unit 108 derives a charging unit price coefficient for each date within the plan derivation period and for each candidate charging station 12.

[0093] For example, the charging unit price coefficient for charging station "A" on October 8th is derived as follows. As described above, the charging unit price for charging station "A" on October 8th is "10." Furthermore, as shown in charging unit price coefficient table 86 in FIG. 4, when the charging unit price is "10," the charging unit price coefficient is "1.6." Therefore, as shown in FIG. 8, a charging unit price coefficient of "1.6" is derived for charging station "A" on October 8th.

[0094] The charging unit price coefficients for other dates within the plan derivation period and for other charging stations 12 among the candidate charging stations 12 are derived in the same manner as the charging unit price coefficient for charging station "A" on October 8th.

[0095] Furthermore, the index derivation unit 108 derives a user orientation coefficient based on the correlation information 82, the user orientation information 80, and the user orientation coefficient table 84. The index derivation unit 108 derives a user orientation coefficient for each date within the plan derivation period and for each candidate charging station 12.

[0096] For example, the user orientation coefficient for charging station "A" on October 8th is derived as follows. For example, assume that user orientation information 80 indicating "environmental priority given" is stored in the storage device 54. As described above, referring to the correlation information 82 in FIG. 2, charging station "A" is a solar renewable energy charging station. Furthermore, as shown in the user orientation coefficient table 84 in FIG. 3, if the user orientation information 80 indicates "environmental priority given" and the charging station is a renewable energy charging station, the user orientation coefficient is "2." Therefore, as shown in FIG. 8, a user orientation coefficient of "2" is derived for charging station "A" on October 8th.

[0097] The user orientation coefficients for other dates within the plan derivation period and for other charging stations 12 among the candidate charging stations 12 are derived in a similar manner to the derivation of the user orientation coefficient for charging station “A” on October 8th.

[0098] Furthermore, the index derivation unit 108 derives a natural disaster coefficient based on the weather forecast information and the natural disaster coefficient table 88. The index derivation unit 108 derives a natural disaster coefficient for each date within the plan derivation period and for each candidate charging station 12.

[0099] For example, the natural disaster coefficient for charging station "A" on October 8th is derived as follows. As shown in FIG. 6, the weather forecast information for October 8th shows that the wind speed is "0" and the rainfall is "0." The wind speed of "0" in this weather forecast information corresponds to the wind speed of "less than 10" in the weather information in the natural disaster coefficient table 88 of FIG. 5. The rainfall of "0" in this weather forecast information corresponds to the rainfall of "less than 10" in the weather information in the natural disaster coefficient table 88 of FIG. 5. As shown in FIG. 5, when the wind speed is "less than 10" and the rainfall is "less than 10," the natural disaster coefficient is "3." Therefore, as shown in FIG. 8, a natural disaster coefficient of "3" is derived for charging station "A" on October 8th.

[0100] The natural disaster coefficients for other dates within the plan derivation period and for other charging stations 12 among the candidate charging stations 12 are derived in the same manner as the natural disaster coefficient for charging station "A" on October 8th.

[0101] The index derivation unit 108 also derives an "index" by multiplying the user preference coefficient, the charging unit price coefficient, and the natural disaster coefficient. The index derivation unit 108 derives an "index" for each date within the plan derivation period and for each candidate charging station 12.

[0102] For example, the "index" for charging station "A" on October 8th is derived as follows. As shown in Fig. 8, at charging station "A" on October 8th, the user preference coefficient is "2", the charging unit price coefficient is "1.6", and the natural disaster coefficient is "3". Therefore, by multiplying the user preference coefficient "2", the charging unit price coefficient "1.6", and the natural disaster coefficient "3", the "index" "9.6" (2 x 1.6 x 3 = 9.6) is derived as shown in Fig. 8.

[0103] The “indicators” for other dates within the plan derivation period and for other charging stations 12 among the candidate charging stations 12 are derived in the same manner as the “indicator” for charging station “A” on October 8th.

[0104] The higher the "index" value, the stronger the reflection of user preferences, the lower the charging cost, and the lower the risk of natural disasters. For this reason, it is preferable to charge under conditions where the "index" value is high.

[0105] The charging plan deriving unit 110 derives a charging plan based on the "index" derived by the index deriving unit 108. The derivation of the charging plan will be described below with reference to Figs.

[0106] Figures 9 to 11 are diagrams showing an example of derivation of a charging plan, and Figures 12 and 13 are diagrams showing another example of derivation of a charging plan.

[0107] Here, it is assumed that the charging plan will perform charging when the SOC of the in-vehicle battery 20 is within a range of 20 to 50. It is also assumed that the charging plan will perform charging until the SOC of the in-vehicle battery 20 reaches 90. It is also assumed that the present is one day before October 8th, and that the current SOC of the in-vehicle battery 20 is 90.

[0108] As shown in FIG. 9, the charging plan derivation unit 110 estimates the transition of the SOC during the plan derivation period based on the SOC decrease amount derived by the SOC decrease amount estimation unit 104.

[0109] For example, as shown in Figure 7, the SOC decrease amount for each day from October 8 to October 12 is "20". From this, as shown in Figure 9, on October 8, the SOC is estimated to have decreased by "20" from "90" to "70". On October 9, the SOC is estimated to have decreased by "20" from "70" to "50". On October 10, the SOC is estimated to have decreased by "20" from "50" to "30". On October 11, the SOC is estimated to have decreased by "20" from "30" to "10". On October 12, the SOC decreases from "10" to "20", resulting in a negative value, and if it is negative, it is estimated to be "0".

[0110] When the SOC transition is estimated as shown in Fig. 9, the SOC "50" on October 9th and the SOC "30" on October 10th fall within the range of 20 to 50, as shown by the bold frame in Fig. 9. Therefore, the charging plan derivation unit 110 determines either October 9th or October 10th as the charging day on which charging will be performed.

[0111] For example, if October 10th is determined as the charging date, as shown in Figure 10, on October 10th, charging will be performed with an amount of charge equivalent to SOC "60" (90-30=60) until the SOC goes from "30" to "90".

[0112] Here, as shown in FIG. 8, the "index" on October 10th is "12," "9.6," "4.8," and "6." Since the maximum value of these "indexes" is "12," the maximum value of the "index" on October 10th, "12," is shown in FIG. 10. Also, as shown in FIG. 8, the charging station 12 corresponding to the maximum value of the "index" on October 10th, "12," is charging station "A." Therefore, as shown in FIG. 10, charging station "A" is shown on October 10th. That is, the charging plan derivation unit 110 determines the charging date, "October 10th," and identifies charging station "A" corresponding to the charging date.

[0113] When charging is performed on October 10th, the SOC after charging on October 10th will be "90", and so the transition of the SOC after charging on October 10th will be updated as shown in FIG.

[0114] For example, as shown in FIG. 7, the SOC decrease amount on October 11th and October 12th is "20", the SOC decrease amount on October 13th is "10", and the SOC decrease amount on October 14th is "30". From this, as shown in FIG. 10, on October 11th, the SOC is estimated to have decreased by "20" from "90" to "70". On October 12th, the SOC is estimated to have decreased by "20" from "70" to "50". On October 13th, the SOC is estimated to have decreased by "10" from "50" to "40". On October 14th, the SOC is estimated to have decreased by "30" from "40" to "10".

[0115] When the SOC transition is updated as shown in Fig. 10, the SOC "50" on October 12 and the SOC "40" on October 13 fall within the range of 20 to 50, as shown by the bold frame in Fig. 10. Therefore, the charging plan derivation unit 110 determines either October 12 or December 13 as the charging day for charging.

[0116] For example, if October 13th is determined to be the charging date, as shown in Figure 11, on October 13th, charging will be performed with an amount of charge equivalent to SOC "50" (90-40=50) until the SOC goes from "40" to "90".

[0117] Here, as shown in FIG. 8, the "index" on October 13 is "7.2," "7.2," "12," and "6." Since the maximum value of these "indexes" is "12," the maximum value of the "index" on October 13 is shown in FIG. 11. Also, as shown in FIG. 8, the charging station 12 corresponding to the maximum value of the "index" on October 13, "12," is charging station "C." Therefore, as shown in FIG. 11, charging station "C" is shown on October 13. That is, the charging plan derivation unit 110 further determines the charging date, "October 13," and identifies charging station "C" corresponding to the charging date.

[0118] When charging is performed on October 13th, the SOC after charging on October 13th will be "90", and so the transition of the SOC after charging on October 13th will be updated as shown in FIG.

[0119] For example, as shown in Figure 7, the amount of decrease in SOC on October 14 is "30." From this, as shown in Figure 11, it is estimated that the SOC on October 14 decreased by "30" from "90" to "60."

[0120] In the example of Fig. 11, within the plan derivation period and beyond October 13th, which has been determined as the earliest charging date, there is no date on which the SOC falls within the range of 20 to 50. As a result, the charging plan derivation unit 110 does not determine any further charging dates.

[0121] Then, the charging plan deriving unit 110 creates a charging plan that includes charging at charging station "A" on October 10th and charging at charging station "C" on October 13th.

[0122] Furthermore, after creating a charging plan, the charging plan derivation unit 110 derives a "total index component" corresponding to the charging plan, and derives a "total index" based on the "total index component." The "total index component" is a value obtained by multiplying the charge amount on a charging day by the maximum value of the "index" on that charging day, and dividing the result by 100. The charging plan derivation unit 110 derives a "total index component" for each charging day. The "total index" is the sum of the "total index components" for each charging day.

[0123] As shown by the bold frame in Figure 11, the "total index component" for the charging date "October 10th" is calculated by multiplying the charge amount "60" by the maximum "index" value "12" and dividing the result by 100, resulting in "7.2" (60 x 12 / 100 = 7.2). The "total index component" for the charging date "October 13th" is calculated by multiplying the charge amount "50" by the maximum "index" value "12" and dividing the result by 100, resulting in "6" (50 x 12 / 100 = 6). Then, as shown by the arrow in Figure 11, the "total index component" "7.2" for the charging date "October 10th" and the "total index component" "6" for the charging date "October 13th" are added together to derive the "total index" "13.2" (7.2 + 6 = 13.2).

[0124] Since the "Comprehensive Index" is derived based on the "Indicators," a higher "Comprehensive Index" indicates a charging plan that more strongly reflects user preferences, has a relatively low charging cost, and is low in risk of natural disasters.

[0125] In the above explanation, of the two candidate charging dates, October 9th and October 10th, which are indicated by the bold frames in FIG. 9, October 10th was determined as the charging date, as shown in FIG. 10. However, in the example of FIG. 9, the charging date can be determined not only on October 10th, but also on October 9th. If the charging date to be determined is different, multiple charging plans with different patterns can be created.

[0126] For example, Fig. 12 shows an example in which October 9th is determined as the charging date out of two candidate charging dates, October 9th and October 10th, which are indicated by bold frames in Fig. 9. As shown in Fig. 12, on October 9th, charging is performed with an amount of charge equivalent to an SOC of "40" (90-50=40) until the SOC goes from "50" to "90".

[0127] Here, as shown in FIG. 8, the "index" on October 9th is "7.2," "7.2," "4.8," and "6." Since the maximum value of these "indexes" is "7.2," FIG. 12 shows the maximum value of the "index" on October 9th, "7.2." Also, as shown in FIG. 8, the charging stations 12 corresponding to the maximum value of the "index" on October 9th, "7.2," are charging station "A" and charging station "B." From this, either charging station "A" or charging station "B" is identified.

[0128] When the maximum values ​​of the "index" are the same for multiple charging stations 12, a charging station 12 may be identified from the multiple charging stations 12 based on a predetermined priority condition. For example, a charging station 12 that is relatively close to the user's home may be identified from the multiple charging stations 12. Note that the priority condition is not limited to the exemplified conditions, and any condition may be set.

[0129] 12, on October 9th, charging station "A" is identified from charging station "A" and charging station "B" based on a predetermined priority condition. That is, the charging plan derivation unit 110 determines the charging date as "October 9th" and identifies charging station "A" corresponding to the charging date.

[0130] When charging is performed on October 9th, the SOC after charging on October 9th will be "90", and so the transition of the SOC after charging on October 9th will be updated as shown in FIG.

[0131] For example, as shown in FIG. 7, the SOC decrease amount on October 10, October 11, and October 12 is "20," the SOC decrease amount on October 13 is "10," and the SOC decrease amount on October 14 is "30." From this, as shown in FIG. 12, on October 10, the SOC is estimated to have decreased by "20" from "90" to "70." On October 11, the SOC is estimated to have decreased by "20" from "70" to "50." On October 12, the SOC is estimated to have decreased by "20" from "50" to "30." On October 13, the SOC is estimated to have decreased by "10" from "30" to "20." On October 14, the SOC decreases from "20" to "30," resulting in a negative value, and if it is negative, it is estimated to be "0."

[0132] When the SOC transition is updated as shown in Fig. 12, the SOC "50" on October 11, the SOC "30" on October 12, and the SOC "20" on October 13 fall within the range of 20 to 50, as shown by the bold frames in Fig. 12. Therefore, the charging plan derivation unit 110 determines that either October 11, October 12, or December 13 is the charging day on which charging will be performed.

[0133] For example, if October 13th is determined to be the charging date, as shown in Figure 13, on October 13th, charging will be performed with an amount of charge equivalent to SOC "70" (90-20=70) until the SOC goes from "20" to "90".

[0134] Here, as shown in FIG. 8, the "index" on October 13 is "7.2," "7.2," "12," and "6." Since the maximum value of these "indexes" is "12," the maximum value of the "index" on October 13 is shown in FIG. 13. Also, as shown in FIG. 8, the charging station 12 corresponding to the maximum value of the "index" on October 13, "12," is charging station "C." Therefore, as shown in FIG. 13, charging station "C" is shown on October 13. That is, the charging plan derivation unit 110 further determines the charging date, "October 13," and identifies charging station "C" corresponding to the charging date.

[0135] When charging is performed on October 13th, the SOC after charging on October 13th will be "90", and so the transition of the SOC after charging on October 13th will be updated as shown in FIG.

[0136] For example, as shown in Figure 7, the amount of decrease in SOC on October 14 is "30." From this, as shown in Figure 13, it is estimated that the SOC on October 14 decreased by "30" from "90" to "60."

[0137] In the example of Fig. 13, within the plan derivation period and beyond October 13th, which has been determined as the earliest charging date, there is no date on which the SOC falls within the range of 20 to 50. As a result, the charging plan derivation unit 110 does not determine any further charging dates.

[0138] Then, the charging plan deriving unit 110 creates a charging plan that includes charging at charging station "A" on October 9th and charging at charging station "C" on October 13th.

[0139] After creating the charging plan, the charging plan deriving unit 110 derives a "total index" corresponding to the charging plan.

[0140] As shown by the bold frame in Figure 13, the "total index component" for the charging date "October 9th" is calculated by multiplying the charge amount "40" by the maximum "index" value "7.2" and dividing the result by 100, resulting in "2.88" (40 x 7.2 / 100 = 2.88). The "total index component" for the charging date "October 13th" is calculated by multiplying the charge amount "70" by the maximum "index" value "12" and dividing the result by 100, resulting in "8.4" (70 x 12 / 100 = 8.4). Then, as shown by the arrow in Figure 13, the "total index component" "2.88" for the charging date "October 9th" and the "total index component" "8.4" for the charging date "October 13th" are added together to derive the "total index" "11.28" (2.88 + 8.4 = 11.28).

[0141] In this manner, the charging plan derivation unit 110 can create a plurality of charging plans with different patterns. Although not described further, in Fig. 10, of the two candidate charging dates, October 12 and October 13, it is possible to create a charging plan with a pattern in which October 12 is the charging date, in addition to the pattern in which October 13 is the charging date shown in Fig. 11. Furthermore, in Fig. 12, of the three candidate charging dates, October 11, October 12, and October 13, it is possible to create a charging plan with a pattern in which either October 11 or October 12 is the charging date, in addition to the pattern in which October 13 is the charging date shown in Fig. 13.

[0142] The charging plan derivation unit 110 identifies the charging plan with the highest "overall index" from among the derived charging plans, and presents the identified charging plan to the user. The charging plan derivation unit 110 presents the identified charging plan to the user, for example, by displaying the charging plan on the display device 70. Note that the method of presenting the charging plan is not limited to this example, and any method may be used, for example, a method of outputting the charging plan by voice.

[0143] In consideration of the above, the charging plan deriving unit 110 derives a plurality of candidate charging plans to be presented to the user. The charging plan deriving unit 110 derives an "overall index" indicating the priority of the candidate charging plans for each candidate charging plan based on the charge amount at the charging timing indicated by the candidate charging plan and the "index." The charging plan deriving unit 110 determines a charging plan to be presented to the user based on the "overall index." The charging plan deriving unit 110 presents the determined charging plan to the user.

[0144] Note that if the user preference is "environmental priority," the charging plan derivation unit 110 will basically derive a charging plan that includes renewable energy charging stations as charging locations. However, even if the user preference is "environmental priority," for example, depending on the influence of a natural disaster coefficient, the "index" value for renewable energy charging stations may become small, and a charging plan that includes non-renewable energy charging stations may be derived. In other words, the charging plan derivation unit 110 reflects the user preference as much as possible and presents the user with the most suitable charging plan overall.

[0145] 14 is a flowchart illustrating the operation of deriving a charging plan in the control device 56. The control device 56 executes a series of processes shown in FIG. 14 when a predetermined interrupt timing occurs at a predetermined cycle.

[0146] When a predetermined interrupt timing arrives, first, the charging plan deriving unit 110 determines whether or not a condition for starting derivation of a charging plan has been satisfied (S10). For example, the charging plan deriving unit 110 determines that the condition for starting derivation of a charging plan has been satisfied when a predetermined time point in one day has passed. Note that the time point is not limited to one day, but may be, for example, two or three days, or may be when a period approximately the same as the plan deriving period, such as one week, has passed. Furthermore, the condition for starting derivation of a charging plan is not limited to this example, and may be set to any content.

[0147] If the conditions for starting derivation of the charging plan are not met (NO in S10), the charging plan deriving unit 110 ends the series of processes.

[0148] When the conditions for starting derivation of a charging plan are satisfied (YES in S10), the charging plan deriving unit 110 sets a plan deriving period, which is a period for deriving a charging plan (S11). The charging plan deriving unit 110 sets, for example, a period of one week from the next day as the plan deriving period.

[0149] Next, the charging plan derivation unit 110 reads the correlation information 82 from the storage device 54 (S12). The charging plan derivation unit 110 extracts candidate charging stations 12 (S13). For example, the charging plan derivation unit 110 determines the charging stations 12 included in the correlation information 82 as the candidate charging stations 12. Note that the method for extracting the candidate charging stations 12 is not limited to this example, and any method may be used.

[0150] Next, the weather forecast information acquisition unit 102 acquires weather forecast information for the area including the candidate charging station from the weather server 60 (S14). The weather forecast information acquisition unit 102 acquires weather forecast information for each day during the plan derivation period.

[0151] Next, the SOC decrease amount estimation unit 104 estimates the SOC decrease amount for each day during the plan derivation period (S15).

[0152] Next, the user-oriented information acquiring unit 106 acquires the user-oriented information 80 (S16). If the user-oriented information 80 is pre-stored in the storage device 54, the user-oriented information acquiring unit 106 reads the user-oriented information 80 from the storage device 54.

[0153] The acquisition of weather forecast information (S14), the estimation of the SOC decrease amount (S15), and the acquisition of user orientation information 80 (S16) are not limited to the order shown in the example, and may be performed in any order.

[0154] Next, the index derivation unit 108 executes an index derivation process (S17). The index derivation process (S17) is a process for deriving an "index" used to derive a charging plan, as described with reference to Fig. 8. The index derivation process (S17) will be described in detail later.

[0155] Next, the charging plan derivation unit 110 executes a charging plan derivation process (S18). The charging plan derivation process (S18) is a process for deriving a charging plan based on the "index" derived in the index derivation process (S17). The charging plan derivation process (S18) will be described in detail later.

[0156] Next, the charging plan deriving unit 110 presents the processing result of the charging plan deriving process (S18) to the user (S19), and ends the series of processes. For example, the charging plan deriving unit 110 causes the display device 70 to display the derived charging plan.

[0157] 15 is a flowchart illustrating the flow of the index derivation process (S17). When the index derivation process (S17) starts, the index derivation unit 108 determines an arbitrary charging station 12 from among the candidate charging stations 12 (S30). Hereinafter, the charging station 12 determined in step S30 may be referred to as the charging station 12 for which the index is to be derived.

[0158] Next, the index derivation unit 108 determines an arbitrary date within the plan derivation period (S31). Hereinafter, the date determined in step S31 may be referred to as the date for which the index is to be derived.

[0159] Next, the index derivation unit 108 refers to the correlation information 82 and estimates the charging cost at the charging station 12 for which the index is to be derived on the date for which the index is to be derived, based on the weather forecast information acquired in step S14 (S32).

[0160] Next, the index derivation unit 108 refers to the charging unit price coefficient table 86 and derives a charging unit price coefficient for the date for which the index is to be derived at the charging station 12 for which the index is to be derived, based on the charging unit price for the date for which the index is to be derived at the charging station 12 for which the index is to be derived (S33).

[0161] Next, the index derivation unit 108 refers to the user orientation coefficient table 84 and derives a user orientation coefficient for the date for which the index is to be derived at the charging station 12 for which the index is to be derived (S34).

[0162] Next, the index derivation unit 108 refers to the natural disaster coefficient table 88 and derives the natural disaster coefficient for the date for which the index is to be derived at the charging station 12 for which the index is to be derived (S35).

[0163] Next, the index derivation unit 108 multiplies the charging unit price coefficient derived in step S33, the user preference coefficient derived in step S34, and the natural disaster coefficient derived in step S35 to derive an "index" for the date for which the index is to be derived at the charging station 12 for which the index is to be derived (S36).

[0164] Next, the index derivation unit 108 determines whether there are any remaining dates in the plan derivation period for which derivation of the "index" has not been completed for the charging station 12 for which the index is to be derived (S37).

[0165] If there are any remaining dates (YES in S37), the index derivation unit 108 returns to step S31 and determines any one of the remaining dates (S31). Then, the index derivation unit 108 repeats the process up to deriving the "index" (S36) for the charging station 12 for which the index is to be derived each time a date is determined in step S31 until there are no remaining dates.

[0166] If there are no remaining dates for the charging station 12 for which the index is to be derived (NO in S37), the index derivation unit 108 determines whether there are any remaining charging stations 12 among the candidate charging stations 12 for which the derivation of the "index" has not been completed (S38).

[0167] If there are any remaining charging stations 12 (YES in S38), the index derivation unit 108 returns to step S30 and determines any one of the remaining charging stations 12 (S30). Then, the index derivation unit 108 repeats the process up to the derivation of the "index" (S36) each time a charging station 12 is determined in step S30, until there are no remaining charging stations 12.

[0168] If there are no remaining charging stations 12 (NO in S38), the index derivation unit 108 ends the index derivation process (S17).

[0169] 16 is a flowchart illustrating the flow of the charging plan derivation process (S18). When the charging plan derivation process (S18) starts, the charging plan derivation unit 110 sets a charging start condition (S50). For example, the charging plan derivation unit 110 sets the charging start condition to be satisfied when the SOC is within a range of 20% to 50%. Note that the charging start condition is not limited to this example and may be set to any SOC range.

[0170] Next, the charging plan deriving unit 110 sets a charging end condition (S51). For example, the charging plan deriving unit 110 sets the charging end condition to be met when the SOC reaches 90% or more. Note that the charging end condition is not limited to this example and may be set to any SOC.

[0171] Next, the charging plan deriving unit 110 estimates the transition of the SOC during the plan deriving period based on the SOC decrease amount derived in step S15 (S52).

[0172] Next, the charging plan deriving unit 110 determines whether there is a date that satisfies the charging start condition after the earliest charging date, based on the transition of the estimated SOC (S53). Note that, if step S53 is performed before step S54 has been performed, the charging plan deriving unit 110 performs the determination of step S53 from the first day of the plan deriving period.

[0173] If there is a date that satisfies the charging start condition (YES in S53), the charging plan deriving unit 110 determines an arbitrary date among the dates that satisfy the charging start condition as the charging date (S54).

[0174] Next, the charging plan derivation unit 110 identifies the maximum value of the "index" for each charging station 12 on the determined charging date (S55). The charging plan derivation unit 110 identifies the charging station 12 corresponding to the maximum value of the "index" (S56). The charging plan derivation unit 110 estimates the charging amount at the identified charging station 12 on the determined charging date based on the transition of the SOC and the charging end condition (S57).

[0175] Next, the charging plan derivation unit 110 returns to step S52 and re-estimates the SOC transition (S52) assuming that charging was performed with the amount of charge estimated in step S57 on the charging date determined in step S54. This updates the SOC transition.

[0176] After the SOC transition is updated, the charging plan derivation unit 110 determines whether there is a date that satisfies the charging start condition among the dates after the charging date determined in step S54 (S53). If there is a date that satisfies the charging start condition here as well (YES in S53), the charging plan derivation unit 110 determines any date among the dates that satisfy the charging start condition as another charging date (S54). That is, by repeatedly performing step S54, the second and subsequent charging dates are also determined.

[0177] If there is a date after the earliest charging date that satisfies the charging start condition, the charging plan derivation unit 110 determines a new charging date and updates the SOC trend, and repeats this process until there is no date after the earliest charging date that satisfies the charging start condition.

[0178] If there are no dates after the earliest charging date that satisfy the charging start condition (NO in S53), the charging plan deriving unit 110 creates a charging plan based on the charging date determined in step S54 and the charging station 12 identified in step S56 (S58). If multiple charging dates are determined in step S54, the charging plan includes the multiple charging dates.

[0179] Next, the charging plan deriving unit 110 derives an "overall index" for the created charging plan based on the charging date and the charging amount in the created charging plan (S59).

[0180] Here, in step S53, if there are multiple dates that satisfy the charging start condition, this corresponds to there being multiple candidate charging dates. In this way, when there are multiple candidate charging dates, charging plans are created for all different patterns of candidate charging dates for each candidate charging date.

[0181] Therefore, after step S59, the charging plan deriving unit 110 determines whether there is another pattern different from the charging plan created in step S58 (S60). For example, if there are multiple dates that satisfy the charging start condition in step S53 and there are patterns among the multiple dates that have not been determined as charging days, the charging plan deriving unit 110 determines that there is another pattern.

[0182] When it is determined that there are other patterns (YES in S60), the charging plan derivation unit 110 repeats step S52 and subsequent steps until there are no other patterns. In this case, a charging plan is created each time step S58 is repeated, and therefore, multiple patterns of charging plans are generated.

[0183] When it is determined that there are no other patterns (NO in S60), the charging plan derivation unit 110 identifies the maximum value of the "overall index" based on the "overall index" for each charging plan (S61).

[0184] The charging plan deriving unit 110 specifies the charging plan corresponding to the maximum value of the "overall index" as the charging plan to be presented to the user (S62), and ends the charging plan deriving process (S18).

[0185] As described above, in the charging management system 1 of this embodiment, a charging plan that reflects the user's preferences and results in a relatively low charging cost is derived based on the correlation information 82, the acquired weather forecast information, the estimated SOC decrease amount, and the acquired user preference information 80.

[0186] The derived charging plan includes charging stations 12 that appropriately reflect the user's preferences, i.e., the driver's preferences. Therefore, if charging is actually performed by referring to the charging plan derived by the charging management system 1 of the present embodiment, charging that takes into account the driver's preferences becomes possible.

[0187] While the present invention has been described above with reference to the accompanying drawings, it goes without saying that the present invention is not limited to such embodiments. It is clear that those skilled in the art can conceive of various modifications and alterations within the scope of the claims, and it is understood that such modifications and alterations also fall within the technical scope of the present invention.

[0188] For example, in the above embodiment, the control device 56 of the vehicle 10 executes the process of generating the correlation information 82 and various processes related to deriving the charging plan. However, any computer external to the vehicle 10 may execute at least one of the process of generating the correlation information 82 and various processes related to deriving the charging plan.

[0189] In the above embodiment, the user preference coefficient, the charging unit price coefficient, and the natural disaster coefficient were set so that the larger the user preference coefficient, the stronger the reflection of the user preference, the larger the charging unit price coefficient, the lower the charging unit price, and the larger the natural disaster coefficient, the lower the risk of natural disasters. However, the user preference coefficient, the charging unit price coefficient, and the natural disaster coefficient may be set so that the smaller the user preference coefficient, the stronger the reflection of the user preference, the lower the charging unit price, and the lower the natural disaster coefficient, the lower the risk of natural disasters. In this case, the charging plan derivation unit 110 presents to the user a charging plan that reduces the "index" and "overall index." [Explanation of symbols]

[0190] 1. Charging management system 10 vehicles 12 Charging Station 20. Car battery 54 Storage device 56 Control device 80 User-oriented information 82 Correlation Information 90 processors 92 memory

Claims

1. a storage device that stores in advance correlation information in which a plurality of charging stations, weather information at the locations of the charging stations at any timing, and a charging unit price at the charging stations at any timing are associated with each other for each of the plurality of charging stations and the plurality of weather information; a control device; Equipped with The control device one or more processors; one or more memories coupled to the processor; and In the correlation information, whether the source of power generation at the charging station is renewable energy or not is associated with each charging station, The processor: obtaining weather forecast information indicative of a weather forecast; Estimating a future decrease in SOC of an on-board battery in a given vehicle; Acquiring user preference information indicating whether a user values ​​charging at a charging station where the source of power generation is renewable energy; deriving a charging plan that indicates a combination of future charging timings and charging locations that will result in a relatively low charging unit price while reflecting the user's preference, based on the correlation information stored in the storage device, the acquired weather forecast information, the estimated SOC decrease amount, and the acquired user preference information; A charging management system that performs processing including:

2. The processor: deriving a user preference coefficient indicative of a weighting of the user preferences based on the user preference information; estimating a charging unit price at the charging station based on the weather forecast information, and deriving a charging unit price coefficient indicating a weighting of the charging unit price at the charging station based on the estimated charging unit price; deriving an index including at least the user orientation coefficient and the charging unit price coefficient; Deriving the charging plan based on the index; The charge management system according to claim 1 , wherein the charge management system executes a process including:

3. The processor: deriving a plurality of candidates for the charging plan to be presented to a user; deriving a comprehensive index indicating a priority of the candidate charging plans for each candidate charging plan based on the charge amount at the charging timing indicated by the candidate charging plan and the index; determining the charging plan to be presented to a user based on the comprehensive index; The charge management system according to claim 2 , wherein the charge management system executes a process including the steps of:

4. The processor: Extracting charging stations based on a route actually taken by the vehicle; Acquiring a charging unit price at a specific timing at the extracted charging station; acquiring weather information at the specific timing at the location of the extracted charging station; generating correlation information by associating the extracted charging stations, the acquired charging unit prices, and the acquired weather information, and storing the generated correlation information in the storage device; The charge management system according to claim 1 , wherein the charge management system executes a process including the steps of:

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